1. Field of the Invention
The present invention relates to processing event records, such as, for example, telecommunications network event records.
2. Related Art
As the telecommunications industry rapidly grows, telecommunications fraud also grows. In the United States alone, telecommunication fraud is estimated to have cost $3 billion in 1995. Telecommunications service providers have experienced difficulty in keeping up with new methods of fraud. As soon as service providers implement new systems to detect current methods of fraud, criminals innovate new methods.
Current methods of fraud are targeted at all types of services. Such services and corresponding fraud include use of calling cards, credit cards, customer premise equipment (CPE), including private branch exchanges (PBX), dial 1+, 800 inbound, and cellular calls. In addition, international dialing is a frequent target of fraud because of its high price of service. Subscription fraud, where a customer subscribes to a service, such as 800 or Dial 1, and then never pays, is also a frequent target of fraud.
Existing methods of detecting fraud are based primarily on setting predetermined thresholds and then monitoring service records to detect when a threshold has been exceeded. Parameters for such thresholds include total number of calls in a day, number of calls less than one minute in duration, number of calls more than 1 hour in duration, calls to specific telephone numbers, calls to specific countries, calls originating from specific telephone numbers, etc. Many parameters can be used to tailor a particular thresholding system for certain customers or services.
These thresholds must be manually programmed, which is labor intensive and time consuming. Moreover, these thresholds are generally subjective and not directly based upon empirical data. In addition, manually programmed thresholds are static and thus do not adjust to changing patterns of fraud. They are therefore easy for criminals to detect and circumvent. Also, since such thresholds must be set conservatively in order to detect most fraud, they are frequently exceeded by non-fraudulent calls, contributing to high rates of false alarms.
When a threshold is exceeded, an alarm is triggered and presented to an analyst, who must then analyze the alarm to determine if it properly reflects fraud. The analyst must query many sources of data, such as customer payment history and service provisioning data, to assess the probability of fraud. The analyst must also assess several different alarms and correlate them to determine if a case of fraud is spanning across services. This manual process of analyzing and correlating is time consuming, labor intensive, highly subjective and prone to error.
When it is determined that fraud has occurred, the analyst must then select an appropriate action and then initiate it. Such actions can include deactivating a calling card or blocking an ANI (Automatic Number Identifier) from originating calls.
Because current systems of fraud management are rigid and generally not configurable for other service providers or industries, new rules, algorithms, routines, and thresholds must constantly be re-programmed.
What is needed is a configurable system, method and computer program product for detecting and automatically acting upon new and evolving patterns and that can be implemented in a variety of applications such as, for example, telecommunications fraud, credit card and debit card fraud, data mining, etc.